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A Quantitative Analysis of Variables Affecting Power Transmission Infrastructure Projects in the US
Reports by Lewis (Zhaoyu) Wu, Abraham Silverman, Harrison Fell + 1 more • April 05, 2024
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Reports by Lewis (Zhaoyu) Wu, Abraham Silverman, Harrison Fell + 1 more • April 05, 2024
This report represents the research and views of the author. It does not necessarily represent the views of the Center on Global Energy Policy. The piece may be subject to further revision. Contributions to SIPA for the benefit of CGEP are general use gifts, which gives the Center discretion in how it allocates these funds. Rare cases of sponsored projects are clearly indicated.
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Upgrading the US electric grid is vital to a successful energy transition. Transmission expansion lowers electricity costs for consumers; speeds deployment of new generation resources; provides economic opportunities for communities; increases system reliability, particularly in the face of extreme weather events; and enables large-scale transfers of power from areas of the country with high renewable energy potential to customers. But experience over the past twenty years has shown that new transmission projects often face extensive delays, impeding or even denying these potential benefits to consumers and communities. In response, policymakers at the state and federal level are considering reforms to transmission finance, cost allocation, siting and permitting, advanced technologies, and other areas to help jumpstart the United States’ currently moribund transmission expansion processes.
As part of this process, policymakers and other stakeholders are debating the merits of various transmission planning policies in terms of project success, but the impact of specific variables can be hard to quantify. This can lead stakeholders to rely largely on anecdotal or qualitative arguments to support their positions. The wide variation in the way utilities are regulated and transmission planning processes are implemented across the United States further compounds the difficulty of evaluating the relative effectiveness of different transmission planning policies.
This report, a joint project of the Non-Technical Barriers to the Clean Energy Transition Initiative and the Energy Systems Modeling and Analytic Platform at the Center on Global Energy Policy, Columbia University SIPA, applies a data-driven approach to this policy debate. Using statistical analysis and machine learning models to analyze a dataset from the data company MAPSearch of planned transmission projects of at least 100 kilovolts (kV) conceived between 2005 and 2023, which includes more than 1,300 transmission projects, the report provides a systematic assessment of the impact of key variables on the likelihood that a proposed transmission line will actually be built. The results of this assessment can help those interested in expanding transmission infrastructure understand which variables may be worth prioritizing in a particular geographical area or region, given its unique combination of attributes, needs, and challenges.
The report finds that the most impactful variables to transmission project success include the following:
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The rapid expansion of artificial intelligence (AI), especially Large Language Models (LLMs) such as GPT-3 and Gemini on which the now well-known ChatGPT AI and Gemina assistant systems...
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Reports by Lewis (Zhaoyu) Wu, Abraham Silverman, Harrison Fell + 1 more • April 05, 2024